System and method for prioritizing migration sequence of data files of an application from a source-storage in a source-system to a target-storage in a target-system in a contact center

A portion of the disclosure of this patent document contains material which is subject to copyright protection. The copyright owner has no objection to the facsimile reproduction by anyone of the patent document or the patent disclosure, as it appears in the Patent and Trademark Office patent file or records, but otherwise reserves all copyright rights whatsoever.

The present disclosure relates to the field of prioritizing migration sequence of data files of an application from a source-storage in a source-system to a target-storage in a target-system in a contact center.

Data migration includes moving data, applications or other business elements to another environment. For example, cloud computing environment. The purpose of the data migration may be reducing costs associated with storage and IT equipment, expanding and scaling storage capacity, improving application performance and user experience, centralizing and simplifying data management and meeting new compliance or security requirements.

Some challenges related to data migration may be ensuring data integrity and security during the transfer, minimizing downtime and disruption to business operations, handling large volumes of data efficiently and combining on-premises infrastructure with public cloud resources.

As contact centers implement cloud services and migrate data of applications the to a computing environment, 33% of organizations see migration time as their biggest concern, with projects often exceeding budgets and timelines. A 2019 survey by Ovum found that data migration is a major challenge for organizations when shifting to cloud-based contact centers.

Data migration requires data retrieval from the source system and then transforming the data by cleaning, formatting and converting it. Then, the transformed data is loaded into the target system.

Transitioning data from one source to another is not an easy task for businesses that daily collect big volumes of structured and unstructured data. According to Oracle, more than 80% of data migration projects fail to meet deadlines or stick to the budget. One of the top four reasons for this happening is that companies neglect data migration challenges and cannot handle the damage these risks bring to their projects. The biggest challenges for migration are in the amount of time it takes for the migration based on the amount of data and the connection bandwidth, allowing for continuing operations during migration, and migration of various data types generated in contact center interactions and files.

Outdated technology may create poor customer experiences. Contact centers implement technologies to ensure business continuity, build resilience, save costs, and gain new efficiencies. The top barriers to cloud migration were centered on existing on-premises contact center investments and security concerns, as well as a resistance to change. A survey found that 31% of consumers have switched brands because a company was lying about product performance (YouGov). 61% of customers say that they would switch to a competitor after only one bad experience. In the case of more than one bad experience, this increases to 80%.

When one the oldest and largest U.S. financial institutions faced regulatory penalties because of its end-of-support infrastructure and application, migrating its contact center to the cloud helped it regain regulatory compliance while improving interactive voice response (IVR) containment and reducing associate training time.

Many times, when switching to a new system the mission-critical data is missing to manage multichannel customer interaction from both customer and agent perspective. Losing business functionalities is often a significant data migration challenge. Company employees and customers may quickly become frustrated by slow-to-respond programs. In addition, data migration solutions that don't involve business users in every step often result in application errors and inefficiencies.

Accordingly, there is a need for a technical solution to smoothly switch to the new system without breaking or disrupting processes and services that have been working well enough for many years and even decades. Mission Critical data missing leads to frustrating employees during the transition phase. They get frustrated as they can't solve customers' problems. According to survey by Frost & Sullivan group, 48% of organizations face this, due to unworkable customer journeys or data which leads to reputational impact, and loss of revenue.

Businesses struggle with limited control and 72% lack awareness of their data, hindering targeted migration and hindering future adaptability. Uncertainty may stagnate a cloud contact center migration strategy.

There is a need for system and method that will prioritize the data migration sequence based on usage criticality and business importance using historical and real-time data analytics and makes an informed decision during the migration of the data.

There is thus provided, in accordance with some embodiments of the present disclosure, a computerized-method for prioritizing migration sequence of data files of an application from a source-storage in a source-system to a target-storage in a target-system in a contact center.

Furthermore, in accordance with some embodiments of the present disclosure, the computerized-method may include: a) for each data file with customers interactions data in the source-storage that has been marked for migration: (i) retrieving metadata of the file and storing the metadata in a metadata-database; (ii) retrieving agents details from an agents-database; (iii) identifying one or more attributes related to customers interactions operations in the stored metadata of the file and agents' details; (iv) receiving a configuration of weights and rules files. The configuration of weights and rules files includes attribute-type associated to each attribute, (v) normalizing value of each attribute in the one or more attributes based on a preconfigured formula that is related to the associated attribute-type; and (vi) operating a file-priority-score module to score priority of the file based on the normalized value of each attribute in the one or more attributes; and b) migrating files to the target-storage in the target-system based on their score of priority.

Furthermore, in accordance with some embodiments of the present disclosure, the attributes related to customers interactions operations may include at least one of: (i) file type; (ii) file size; (iii) interaction duration; (iv) file age; (v) period since last accessed; (vi) access frequency; (vii) agent; and (viii) team, and the agents details include for each agent at least one of: (i) agent team priority; and (ii) agent proficiency level.

Furthermore, in accordance with some embodiments of the present disclosure, the data migration may be to a cloud storage and the contact center may be a cloud-based contact center. The attributes related to customers interactions operations further include tenant tier and tenant size.

Furthermore, in accordance with some embodiments of the present disclosure, the computerized-method may further include retrieving tenant tier and tenant size from a tenant-metadata database.

Furthermore, in accordance with some embodiments of the present disclosure, the attribute-type is one of: (i) maximization-attribute; and (ii) minimization-attribute.

Furthermore, in accordance with some embodiments of the present disclosure, the files in the source-storage with customers interactions data that has been marked for migration are files that have been generated during a preconfigured period.

Furthermore, in accordance with some embodiments of the present disclosure, the configuration of weights and rules files further includes a weight associated to each attribute in the one or more attributes, and the file-priority-score module may include: (i) calculating a weighted product of each normalized value of the attribute in the one or more attributes based on the associated weight; and (ii) calculating a sum of weighted products of the one or more attributes to yield a score to the file. Each attribute may be assigned a default weight, and the weighted product may be calculated accordingly.

Furthermore, in accordance with some embodiments of the present disclosure, the attribute-type and weight associated to each attribute in the configuration of weights and rules files determine a level of significance and usage criticality of the file during customers interactions operations.

Furthermore, in accordance with some embodiments of the present disclosure, the computerized-method may further include operating the application via the target-system after a preconfigured number of data files from all data files in the source-storage have been migrated to the target-storage.

Furthermore, in accordance with some embodiments of the present disclosure, the computerized-method may further include checking operation of the application with the preconfigured number of files that have been migrated to the target-storage. The checking may include: (i) operating the application for a preconfigured subset of customers; (ii) testing the application by operating at least one of: a. data integrity tests; and one or more recommended tests; (iii) determining a failure migration of the preconfigured number of files that have been migrated to the target-storage when the data integrity tests have failed and when the data integrity tests were successful, and the one or more recommended tests have failed; and (iv) determining a successful migration of the preconfigured number of files that have been migrated to the target-storage when the data integrity tests, and one of the one or more recommended tests have been successful.

Furthermore, in accordance with some embodiments of the present disclosure, the one or more recommended tests may include: a. core functionality tests; b. performance testing; and c. user experience testing.

Furthermore, in accordance with some embodiments of the present disclosure, when determining the failure migration, the computerized-method may further include stopping the migrating files to the target-storage in the target-system based on their score of priority and operating corrective actions.

In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the disclosure. However, it will be understood by those of ordinary skill in the art that the disclosure may be practiced without these specific details. In other instances, well-known methods, procedures, components, modules, units and/or circuits have not been described in detail so as not to obscure the disclosure.

Although embodiments of the disclosure are not limited in this regard, discussions utilizing terms such as, for example, “processing,” “computing,” “calculating,” “determining,” “establishing”, “analyzing”, “checking”, or the like, may refer to operation(s) and/or process(es) of a computer, a computing platform, a computing system, or other electronic computing device, that manipulates and/or transforms data represented as physical (e.g., electronic) quantities within the computer's registers and/or memories into other data similarly represented as physical quantities within the computer's registers and/or memories or other information non-transitory storage medium (e.g., a memory) that may store instructions to perform operations and/or processes.

Although embodiments of the disclosure are not limited in this regard, the terms “plurality” and “a plurality” as used herein may include, for example, “multiple” or “two or more”. The terms “plurality” or “a plurality” may be used throughout the specification to describe two or more components, devices, elements, units, parameters, or the like. Unless explicitly stated, the method embodiments described herein are not constrained to a particular order or sequence. Additionally, some of the described method embodiments or elements thereof can occur or be performed simultaneously, at the same point in time, or concurrently. Unless otherwise indicated, use of the conjunction “or” as used herein is to be understood as inclusive (any or all of the stated options).

The term ‘Agent’ as used herein refers to the contact center personnel who handled the interaction stored in the file being migrated. Various attributes related to the agent may be considered, such as, related team and skills.

Current contact centers are making great efforts to adopt new contact center solutions which involve contact center data migration from current system to the target system. Outdated technology may cause poor customer experiences. Contact center migration is now a priority for many organizations. Today, businesses undertake different types of data center modernization to ensure business continuity, build resilience, save costs, and gain new efficiencies.

Top barriers to data migration and particularly to cloud migration were centered on existing on-premises contact center investments and security concerns, as well as a resistance to change. A survey found that 31% of consumers have switched brands because a company was lying about product performance. 61% of customers say that they would switch to a competitor after only one bad experience. In the case of more than one bad experience, this increases to 80%.

There are also costs associated with a lack of agility to shift easily with market changes, including the recent economic downturn, or internal shifts in strategy, such as delaying migration with the same outcome. Higher costs, a less competitive business and an impact to the brand.

When one of the oldest and largest U.S. financial institutions faced regulatory penalties because of its end-of-support infrastructure and application, migrating its contact center to the cloud helped it regain regulatory compliance while improving interactive voice response (IVR) containment and reducing associate training time.

Losing business functionalities is often a significant data migration challenge. Company employees and customers can quickly become frustrated by slow-to-respond programs. In addition, data migration solutions that don't involve business users in every step often result in application errors and inefficiencies.

Current solutions for data migration include manual data migration, scripted migration, commercial migration tools and cloud migration services. Manual data migration involves manual transferring of data from the source system to the target system. While simple, it is time-consuming, error-prone, and does not prioritize files based on their importance or relevance. Scripted migration involves writing scripts or code to automate parts of the migration process. While more efficient than manual migration, it still lacks the ability to prioritize files based on their significance and adapt to changing priorities. Commercial migration tools that offer automated data migration capabilities often provide basic functionality for transferring data but may not offer advanced prioritization or customization options. Cloud migration services offered by some cloud service providers to help businesses move their data to the cloud computing environment. While these services can be efficient, they may not prioritize files based on their importance or adapt to the specific needs of contact center data migration.

While these existing solutions offer some level of automation and efficiency, they often lack the advanced prioritization, dynamic adaptability, and customization capabilities.

There is a need for a technical solution to smoothly make the move without breaking or disrupting processes and services that have been working well enough for many years, even decades. When mission critical data is missing it may lead to frustrating employees during the transition phase. They get frustrated as they can't solve customers' problems due to unworkable customer journeys or data which leads to reputational impact, and loss of revenue.

Businesses struggle with limited control and a major portion of them lack awareness of their data, hindering targeted migration and hindering future adaptability. Uncertainty stagnates a cloud contact center migration strategy, which may be a costly mistake. Not migrating the data may have financial implications and it may halt the ability to innovate.

Instead of spending months on drafting data migration strategy, there is a need for a technical solution that will provide the ability to prioritize the data migration sequence based on usage criticality and business importance using historical and real-time data analytics and will make an informed decision during the migration of the data.

There is a need for a system and method for prioritizing migration sequence of data files of an application from a source-storage in a source-system to a target-storage in a target-system in a contact center. For example, for the following scenarios. When legacy systems become outdated, companies opting for technological advancements. It may be due to better performance and security features, or could be compliance, or cost-related factors. Mergers and acquisitions are also a very common phenomenon in the contact center domain.

schematically illustrates a high-level diagram of a systemfor prioritizing migration sequence of data files of an application from a source-storage in a source-system to a target-storage in a target-system in a contact center, in accordance with some embodiments of the present disclosure.

According to some embodiments of the present disclosure, a system, such as systemmay address shortcomings of current solutions by providing a predictive ranking algorithm tailored for contact center files, dynamic prioritization mechanisms, and advanced automation features. Files that have been marked for migration are evaluated and assigned a priority score based on business needs and predefined criteria which is reflected in attributes and the assigned related weight. Those with higher scores are prioritized and selected for migration first, thus, ensuring an optimized and efficient migration process.

According to some embodiments of the present disclosure, systemmay prioritize migration sequence of data files of an applicationfrom a source-storagein a source-systemto a target-storagein a target-systemin a contact center. The prioritization may overcome the challenge of losing business functionalities as in current solutions many times, when switching to a new system the mission-critical data is missing to manage multichannel customer interaction from both customer and agent perspective.

According to some embodiments of the present disclosure, unlike many existing data migration solutions that employ generic or one-size-fits-all prioritization methods, systemprovides a tailored approach. It incorporates a predictive ranking algorithm specifically designed for contact center files, considering attributes such as file size, frequency of access, and relevance to ongoing operations. This customized prioritization ensures that the data migration efforts focus on the most critical data, minimizing disruptions and optimizing efficiency.

According to some embodiments of the present disclosure, systemmay prioritize the data migration sequence based on usage criticality and business importance using historical and real-time data analytics, e.g., file attributes identified in the metadata and agents details to score the priority of the file during the migration of the data. In a cloud-based environment, tenant tier and size may be included in the attributes of the file.

According to some embodiments of the present disclosure, in a multi-tenant environment tenants may be ranked as per their business value, interaction volumes, and service level agreements (SLAs). This rank may be used during the data migration.

According to some embodiments of the present disclosure, systemmay calculate the file priority score accordingly, to ensure that critical files from high-value tenants may be migrated first to minimize disruption and maintain service continuity.

According to some embodiments of the present disclosure, for each data file with customers interactions data in the source-storagein the source-systemthat has been marked for migration retrieving metadata of the file and storing the retrieved metadata in a metadata-database.

According to some embodiments of the present disclosure, the retrieved metadata may include basic information, such as file name, file type, file size and location. Date related details, such as creation date, last modified date and last accessed date. Author information, permissions, such as access rights and permissions, who can read, write or execute the file. Technical details, such as duration and bit rate and tags and keywords for categorization and search of the file.